To install the software, first download the above zip file to your computer (Windows machines only) and
extract the installation folder. Then run SOM->Package->setup.exe to start the installation wizard.

K-Means Demo: Demonstrates the K-Means clustering algorithm.
The application generates random data and then users can step through the algorithm, viewing the intermediate results.
See below for instructions.
Design and Implementation: Michael Rice, Wesleyan University.

To install the software, first download the above zip file to your computer (Windows machines only) and
extract the installation folder. Then run KMeansDemo->Package->setup.exe to start the installation wizard.

Teaching Demo Instructions

SOM Demo

The RGB values (e.g. (100, 255, 255)) in each square in the grid
represent a model vector of theoretical expression values in three microarrays.

The model vectors in the grid are updated in each iteration based on
fixed expression vectors for genes. (Note that the gene expression
vectors are not shown in the demo.) Using the SOM algorithm, only
the model vector closest to each gene vector, and the grid squares
within the radius distance, are updated.

(a) - To update the grid based on one data point (gene) at a time,
press "Update One"
(b) - To update the grid based on all data points (genes) at once,
press "Update All"

Continue updating until the grid values stabilize
(Note the number of iterations and pattern of colors
representing RGB model vectors of gene expression)

Once the model vectors in the grid have stabilized, each gene is
assigned to the closest model vector (grid square), thereby defining clusters

You may explore the effects of varying parameters; for example,
try using 100 data points (genes)

[* The "Create Grid" button assigns random values to each model vector
in the grid and initializes the RGB value for each data point (gene)
to the same value if the number of data points (genes) is not changed.
The "Create Grid (R)" button initializes the RGB values for each data
point (gene) to random values. ]

K-Means Demo

Click add random data (should put specified number of points in first panel).

At this point, the three option buttons below the button you just
clicked should have the "add means" selected. If not, select that option
and then click at a few points in the first panel to add the initial
positions of the green means.

Click "distribute data" to see the clusters visually in the first panel.

Click in the second panel and then click "update means" to display the
data points and positions of new means in the second panel.